Book Image

Python Architecture Patterns

By : Jaime Buelta
Book Image

Python Architecture Patterns

By: Jaime Buelta

Overview of this book

Developing large-scale systems that continuously grow in scale and complexity requires a thorough understanding of how software projects should be implemented. Software developers, architects, and technical management teams rely on high-level software design patterns such as microservices architecture, event-driven architecture, and the strategic patterns prescribed by domain-driven design (DDD) to make their work easier. This book covers these proven architecture design patterns with a forward-looking approach to help Python developers manage application complexity—and get the most value out of their test suites. Starting with the initial stages of design, you will learn about the main blocks and mental flow to use at the start of a project. The book covers various architectural patterns like microservices, web services, and event-driven structures and how to choose the one best suited to your project. Establishing a foundation of required concepts, you will progress into development, debugging, and testing to produce high-quality code that is ready for deployment. You will learn about ongoing operations on how to continue the task after the system is deployed to end users, as the software development lifecycle is never finished. By the end of this Python book, you will have developed "architectural thinking": a different way of approaching software design, including making changes to ongoing systems.
Table of Contents (23 chapters)
2
Part I: Design
6
Part II: Architectural Patterns
12
Part III: Implementation
15
Part IV: Ongoing operations
21
Other Books You May Enjoy
22
Index

Python introspection tools

As Python is a dynamic language, it's very flexible and allows you to perform actions on its objects to discover their properties or types.

This is called introspection, and allows you to inspect elements without having too much context about the objects to be inspected. This can be performed at runtime, so it can be used while debugging to discover the attributes and methods of any object.

The main starting point is the type function. The type function simply returns the class of an object. For example:

>>> my_object = {'example': True}
>>> type(my_object)
<class 'dict'>
>>> another_object = {'example'}
>>> type(another_object)
<class 'set'>

This can be used to double-check that an object is of the expected type.

A typical example error is to have a problem because a variable can be either an object or None. In that case, it's possible...